Table of Contents

• Coverage
• Dataset Description
  • Methods & Sampling
  • Data Processing Description
  • BCO-DMO Processing Description
• Data Files
• Related Publications
• Parameters
• Instruments
• Project Information
• Funding

Seawater samples were collected during a South African Department of Forestry, Fisheries and Environment (DFFE) Integrated Ecosystem Programme cruise aboard the FRV Mirabilis in February 2017 along 14 stations across the St Helena Bay Monitoring Line (~32.5°S) and the Columbine upwelling cell. Hydrographic profiles were obtained using a Sea-Bird SBE 911 CTD with oxygen sensors and 12 x 6-liter (L) Niskin bottles. Oxygen sensors were calibrated against discrete Winkler titrations. Seawater for nutrient analysis (NO₃⁻+NO₂⁻, NO₂⁻, PO₄³⁻, Si(OH)₄) was collected following GO-SHIP protocols, frozen at -20 degrees Celsius (°C), and analyzed using flow injection analysis (FIA) and manual colorimetric methods. NH₄⁺ was determined fluorometrically using OPA derivatization immediately after collection.

N₂O samples were collected in 125-milliliter (mL) gas-tight glass bottles, preserved with saturated HgCl₂, and stored inverted at room temperature. Concentrations and isotopic compositions (δ¹⁵N-N₂O and δ¹⁸O-N₂O) were determined using a continuous-flow isotope ratio mass spectrometer (CF-MC-IRMS) following Bourbonnais et al. (2017) and McIlvin & Casciotti (2011). Calibration included internal seawater standards and N₂O reference gases spanning a wide isotopic range. Derived variables include apparent oxygen utilization (AOU), N-deficit (based on AOU–NO₃⁻ stoichiometry), and N₂O saturation disequilibrium (ΔN₂O), with equilibrium concentrations estimated from Weiss & Price (1980) using atmospheric N₂O histories from Liu & Tanhua (2024).

Data were processed using Ocean Data View (Schlitzer, 2016).

- Imported original file "Wallschuss_data.xlsx" into the BCO-DMO system.
- Marked "#N/A" as a missing data value (note that missing data are empty/blank in the final CSV file).
- Renamed fields to comply with BCO-DMO naming conventions.
- Converted Date column to YYYY-MM-DD format.
- Created date-time column in ISO 8601 format.
- Saved the final file as "969121_v1_n2o_isotopes.csv".

NSF Award Abstract:
Nitrous oxide is a long-lived and powerful greenhouse gas. It is also a driver of ozone depletion in the stratosphere. Natural sources of nitrous oxide include production by bacteria through processes called nitrification and denitrification. The ocean is a major source of nitrous oxide to the atmosphere, and areas of high biological productivity like eastern boundary upwelling systems have been shown to generate particularly high nitrous oxide emissions to the atmosphere. The Southern Benguela Upwelling System (SBUS) is arguably the most productive eastern boundary upwelling system, yet there are no published measurements of nitrous oxide from this region. In addition, the relative importance of the major biological pathways of nitrous oxide production in the SBUS is not well established. A team of scientists from the University of Connecticut and the University of South Carolina will investigate nitrous oxide cycling in the SBUS, estimate nitrous oxide fluxes to the atmosphere, and explore what drives changes in nitrous oxide cycling across seasons and in different locations. This study will improve understanding of an important greenhouse gas and how its cycling might change in response to changing ocean conditions. Funding from the proposed work will sponsor the training of a graduate student at the University of Connecticut and an undergraduate student at the University of South Carolina. It will also provide a postdoctoral fellow the opportunity to apply computational skills in regional modeling and machine learning, offering preparation for a career in academia or industry. The project will contribute to undergraduate education and communication of climate change science to the general public and policymakers through the incorporation of the study methodology into an undergraduate Service Learning course at the University of Connecticut.

This work seeks to provide estimates of the regional flux of nitrous oxide to the atmosphere, to examine seasonal dynamics, to assess the biological pathways to nitrous oxide production and consumption, and to query regional and large scale forcings on nitrous oxide dynamics in the SBUS. To this end, the team will (a) measure nitrous oxide concentrations in samples collected in the SBUS during seasonal surveys, measure surface nitrous oxide continuously underway, and derive robust estimates of the sea-to-air flux of nitrous oxide from coincident windspeed; (b) query nitrous oxide production and consumption pathways from measurements of the nitrogen and oxygen isotope ratios of nitrous oxide and nitrate, and investigate environmental correlates of nitrous oxide cycling; (c) develop regional machine learning models for nitrous oxide from these measurements to investigate environmental drivers of seasonal and inter-annual nitrous oxide dynamics, predicting nitrous oxide in the SBUS with historical data and with hydrographic fields derived from a regional dynamical ocean model. The work will give insights into pathways of nitrous oxide production and consumption in an eastern boundary upwelling system bounded by a broad continental shelf – contrasting the greater body of knowledge obtained from active margins. The statistical nitrous oxide models borne of machine learning will ultimately serve to predict nitrous oxide from climate projections of the SBUS, and to anticipate the regional response of nitrous oxide to global ocean de-oxygenation.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.